The present invention relates generally to the field of query processing, and more particularly to context sensitive query expansion.
The fields of information retrieval and natural language processing may benefit from many of the same techniques. A natural language user query input to a search engine system may be analyzed and modified so as to increase the likelihood of a correct response being returned. Example techniques include: synonym expansion; word sense disambiguation; and spell correction.
A query is modified or expanded to include new words, or variations of existing words, in order to improve the recall of the system. Such a modification or expansion can involve generalizing the query such that: with synonym expansion, alternative text can be found with the same meaning and update the query accordingly. With word-sense disambiguation, the meaning of a word can be located in the context of the query, so that results that are not relevant to this context can be filtered out. Other technologies exist that leverage semantic graphs for query expansion, that use concepts discovered in the query to traverse a graph's structure in order to help identify other related concepts (and as a result alternative query text) which are semantically related to the original query. The use of data from these related concepts increase the likelihood that a useful result will be returned. For example “school of dolphins” in a search query could be coupled with or replaced with “pod of dolphins” and/or “educational institution of dolphins”.